20 citations · 50 across the 14 of their papers we have counts for
11 papers · 1 filter
On Model and Data Scaling for Skeleton-based Self-Supervised Gait Recognition
Adrian Cosma, Andy Cǎtrunǎ, Emilian Rǎdoi
Gait recognition from video streams is a challenging problem in computer vision biometrics due to the subtle differences between gaits and numerous confounding factors. Recent adva…
Reading Between the Frames: Multi-Modal Depression Detection in Videos from Non-Verbal Cues
David Gimeno-Gómez, Ana-Maria Bucur, Adrian Cosma +2
Depression, a prominent contributor to global disability, affects a substantial portion of the population. Efforts to detect depression from social media texts have been prevalent,…
GaitFormer: Learning Gait Representations with Noisy Multi-Task Learning
Adrian Cosma, Emilian Radoi
Gait analysis is proven to be a reliable way to perform person identification without relying on subject cooperation. Walking is a biometric that does not significantly change in s…
Learning to Simplify Spatial-Temporal Graphs in Gait Analysis
Adrian Cosma, Emilian Radoi
Gait analysis leverages unique walking patterns for person identification and assessment across multiple domains. Among the methods used for gait analysis, skeleton-based approache…
PsyMo: A Dataset for Estimating Self-Reported Psychological Traits from Gait
Adrian Cosma, Emilian Radoi
Psychological trait estimation from external factors such as movement and appearance is a challenging and long-standing problem in psychology, and is principally based on the psych…
GaitPT: Skeletons Are All You Need For Gait Recognition
Andy Catruna, Adrian Cosma, Emilian Radoi
The analysis of patterns of walking is an important area of research that has numerous applications in security, healthcare, sports and human-computer interaction. Lately, walking…